LLMOps: Converting Fine-Tuned ViT Classifier to ONNX for CPU Inference
Convert a fine-tuned ViT Transformer to ONNX format and perform CPU inference, enhancing model portability and efficiency for custom image classification tasks.
LLMOps: Comparison of OpenVino, ONNX, TensorRT, and PyTorch Inference
Explore model conversion to ONNX, OpenVino, and Tensor-RT formats for optimized CPU and GPU inference, comparing performance against native PyTorch.
LLMOPs: Multimodal Prompting and Inference with Phi-3 Vision 128K Instruct on CPU - ONNX 4-Bit Quantization in C#
Explore multimodal prompting and CPU inference using Phi 3 Vision 128K Instruct, quantized to 4 bits in ONNX format, with C# implementation for efficient machine learning operations.
LLMOPs - Inference in CPU with Phi3 4k Instruct ONNX 4-bit Model Using C#
Explore CPU-based inference using 4-bit quantized Phi 3 4K Instruct in ONNX format with C#. Learn practical implementation for efficient machine learning deployment.
LLMOps: Converting Video Classifier (ViViT) to ONNX and Inference on CPU
Convert a Video Vision Transformer to ONNX format and perform CPU inference, enhancing model portability and deployment flexibility for video classification tasks.
Making Sense of LLMOps - Impact, Risk, and Maturity Assessment
Explore LLMOps essentials: impact assessment, risk management, and maturity evaluation. Gain insights on bridging gaps between data science, infrastructure, and IT teams for effective LLM deployment.
Navigating the Emerging LLMOps Stack
Explore the emerging LLMOps Stack, including tools and best practices for maximizing LLM potential in organizations. Gain insights from an experienced AI/ML engineering leader.
Bridging MLOps and LLMOps: Integrating Governed Generative AI into Enterprise Systems
Explore MLOps and LLMOps integration for enterprise Generative AI, addressing risk and compliance. Learn to adapt existing frameworks and build efficient LLM-based applications.
SKT LLM Enterprise 서비스 - 기업용 맞춤형 LLM 최적화 솔루션
Discover SKT의 맞춤형 LLM Enterprise 서비스 개발 과정과 기술적 접근 방식을 통해 기업 환경에 최적화된 AI 솔루션 구현 방법을 탐구하는 기술 세션
How to Improve LLM Factual Accuracy and Reliability
Explore techniques for improving LLM factual accuracy, including DSP framework and MLflow LLMOps tools, to create reliable AI applications for production use.
LLMOps and GenAI at Enterprise Scale - Challenges and Opportunities
Explore challenges and opportunities in deploying GenAI solutions at enterprise scale. Learn about LLMOps, model selection, emerging stacks, and best practices for robust implementation.
LLMOps: Inference of Fine-Tuned ViT Classifier on CPU with C#
Perform CPU inference on a fine-tuned Vision Transformer using C# and ONNX format for efficient image classification in machine learning projects.
LLMOps and FMOps for E-commerce - Booking.com Case Study
Explore MLOps evolution in e-commerce, focusing on LLMs' impact, key investments, and real-world examples from Booking.com's AI implementation and scaling challenges.
vLLM Inference and LLM Server Engine for Machine Learning
Discover how to leverage vLLM for efficient large language model inference and serving, including practical implementation techniques and deployment strategies.
Operational Excellence for LLMs Using Amazon Bedrock - Conf42 LLMs 2024
Explore operational excellence for LLMs using Amazon Bedrock. Learn design principles, LLMOps, model lifecycle, customization, and architectural patterns for effective implementation and evaluation.
MLOps and LLMOps: From Prompt to Observability - Lecture 1
Explore MLOps, AI observability, and LLMOps integration. Gain insights on implementing AI stores for enhanced management and governance of traditional and generative AI solutions across organizations.
The Emerging Toolkit for Reliable, High-quality LLM Applications
Explore emerging techniques in LLMOps for building, tuning, and maintaining high-quality LLM applications. Learn about testing tools, programming frameworks, and methods to control LLM outputs for desired goals.
Founding, Funding, and the Future of MLOps - MLOps Podcast Episode 200
Explore MLOps, AI-driven creativity, and the future of technology with Storia AI co-founder Mihail Eric. Gain insights on LLMs, image generation, and AI's impact across industries.
Charting LLMOps Odyssey - Navigating Large Language Model Operations
Navigate the iterative development of LLM applications, addressing unique challenges in LLMOps design. Learn strategies for overcoming obstacles and adapting to the evolving landscape of large language model operations.
Fine-Tuning ViT Classifier with Custom Data and Docker Inference - Part 4
Fine-tune a ViT classifier with custom data and deploy using Docker and FastAPI for efficient image classification in production environments.
The Science of LLM Benchmarks: Methods, Metrics, and Meanings
Explore LLM benchmarks, evaluation metrics, and critical assessment techniques to understand model strengths and limitations in this comprehensive talk on AI performance evaluation.